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Modeling Computation

Modeling Computation. Chapter 13. Chapter Summary. Languages and Grammars Finite-State Machines with Output Finite-State Machines with No Output Language Recognition Turing Machines. Languages and Grammars. Section 13.1. Section Summary. Phrase-Structure Grammars

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Modeling Computation

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  1. Modeling Computation Chapter 13

  2. Chapter Summary • Languages and Grammars • Finite-State Machines with Output • Finite-State Machines with No Output • Language Recognition • Turing Machines

  3. Languages and Grammars Section 13.1

  4. Section Summary • Phrase-Structure Grammars • Types of Phrase-Structure Grammars • Derivation Trees • Backus-Naur Form

  5. Introduction • Syntax (form of a sentence) vs. semantics (meaning of a sentence) • The sentence the frog writes neatly is a valid sentence according to the rules of English grammar. That is, it is syntactically correct, even though it’s nonsensical (unless we are talking about a fantasy world). • The sequence of words swims quickly mathematics is not a valid sentence according to the rules of English grammar.

  6. Grammars • The rules that specify the syntactically correct sentences of a natural language such as English are complex. • Instead of studying natural languages, we can define formal languages that have well-defined rules of syntax. • These rules of syntax are important both in linguistics (the study of natural languages) and in the study of programming languages.

  7. An Example Grammar • asentence is made up of a noun phrase followed by a verb phrase; • anoun phrase is made up of an article followed by an adjective followed by a noun, or • a noun phrase is made up of an article followed by a noun; • a verb phrase is made up of a verb followed by an adverb, or • a verb phrase is made up of a verb; • an article is a, or • an article is the; • an adjective is large, or • an adjective is hungry; • anoun is rabbit, or • a noun is mathematician; • averb is eats, or • a verb is hops; • an adverb is quickly, or • an adverb is wildly. We use these rules to form valid sentencesby making a series of replacements until no more rules can be used. An example sequence of replacements: noun phrase verb phrase article adjective noun verb phrase article adjective noun verb adverb theadjective noun verb adverb the large noun verb adverb the large rabbit verb adverb the large rabbit hops adverb the large rabbit hops quickly Some additional valid sentences are: a hungry mathematician eats wildly, a large mathematician hops, the rabbit eats quickly, etc. But note that the following is not valid: the quickly eats mathematician

  8. Phrase-Structure Grammars • A vocabulary (or alphabet) V is a finite, nonempty set of elements called symbols. • A word (or sentence) over V is a string of finite length of elements of V. • The empty string or null string, denoted by λ, is the string containing no symbols. • The set of all words over V is denoted by V*. A language over V is a subset of V*. • The elements of V that can not be replaced by other symbols are called terminals, e.g., a, the, and rabbit in the example grammar. • Those that can be replaced by other symbols are called nonterminals, e.g., sentence, noun phrase, etc. • The rules that specify when we can replace a string V* with another string are called productions of the grammar. We denote by z0→z1 the production that specifies that z0 can be replaced by z1 within a string.

  9. Phrase-Structure Grammars (cont.) • A phrase-structure grammarG =(V, T, S, P) consists of a vocabulary V, a subset T of V consisting of terminal symbols, a start symbol S from V, and a finite set of productions P. • The setN =V−T is the set of nonterminal symbols. • Every production in P must contain at least one nonterminal on its left side. ***Example (Grammar 1): Let G =(V, T, S, P), where V = {a, b, A, B, S}, T = {a,b}, S is the start symbol, and P = {S→Aba, A →BB, B →ab, AB →b}.

  10. Derivations • Let G =(V, T, S, P) be a phrase-structure grammar. Let w0 = lz0r (that is the concatenation of l, z0, and r) and w1 = lz1r be strings over V. If z0 → z1 is a production of G, we say that w1 is directly derivable from w0and write w0⇒w1. • If w0,w1, ...,wn are strings over V such that w0⇒w1, w1⇒w2, …, wn-1⇒wn, then we say that wn is derivable from w0and write w0 wn. • The sequence of steps used to obtain wn from w0 is called a derivation. Example (Grammar 1): Aabais directly derivable from ABabecause B →abis a production and abababais derivable from ABabecause ABa⇒Aaba⇒BBaba⇒Bababa ⇒abababa using the productions B→ab,A →BB, andB →abin both of the last two steps of the derivation.

  11. Language Generation • Let G =(V, T, S, P) be a phrase-structure grammar. The language generated by G, denoted by L(G), is the set of all strings or terminals that are derivable from the starting state S. • In other words, L(G) = {w∈T* | S w}. • Let G be the grammar with the vocabulary V = {S, A, a, b}, a set of terminals T = {a, b}, starting symbol S, and productions P = {S → aA, S → b, A → aa}. • L(G) = {b, aaa}, because we can begin a derivation with S→ aAorwith S → b, andfrom aAwe can derive aaa using A→ aa. There are no other possible derivations.

  12. Types of Phrase Structure Grammars Avram Noam Chomsky (Born 1928) • Phrase-structure grammars are classified by the types of allowable productions. • Type 2 grammars are called context-free grammars. A language generated by a context-free grammar is called a context-free language. • Type 3grammars are called context-sensitive grammars (or a regular grammar).Alanguage generated by a context-sensitive grammar is called a context-sensitive language (or a regular language).

  13. Derivation Trees • We can represent a derivation in the language generated by a context-free grammar by an ordered rooted tree, called a derivation, or parse tree. • The root of the tree represents the start symbol. • The internal vertices represent the nonterminal symbols that arise in the derivation. • The leaves represent the terminal symbols that arise. • If the production A→w, where w is a word, arises in the derivation, the vertex that represents A has as children vertices that represent each symbol in w, in order from left to right. • A derivation tree for the derivation of the hungry rabbit eats quickly, given the grammar described earlier.

  14. Backus-Naur Form Peter Naur (Born 1928) John Backus (1924-2007) • Backus-Naur form (BNF)is sometimes used to specify a type 2 grammar. It is often used to specify the syntactic rules of computer languages. • The productions of a type 2grammar have a single nonterminal symbol on their left-hand side. • All the productions with the same nonterminal symbol on the left-hand side are combined into one statement using the symbol ::= instead of →. Additionally,, all nonterminal symbols are enclosed in brackets (〈〉), and the right-hand side of productions are spearated by bars. • For example, the productions A→Aa, A→a, andA →ABare written as 〈A〉 ::= 〈A〉a | a | 〈A〉〈B〉.

  15. BNF and ALGOL 60 • In the programming language ALGOL 60 an identifier consists of a string of alphanumeric characters and must begin with a letter. • The BNF description of allowable identifiers is: 〈identifier〉 ::=〈letter〉 |〈identifier〉〈letter〉 | 〈identifier〉〈digit〉 〈letter 〉 ::= a | b | ⋯ | y | z 〈digit〉 ::= 0 | 1 | ⋯ | 8 | 9 • x99a is a valid identifier since the first rule can be used to replace 〈identifier〉 by 〈identifier〉〈letter〉 , the second rule to obtain 〈identifier〉a, the first rule twice to obtain 〈identifier〉〈digit〉〈digit〉a, the third rule twice to obtain 〈identifier〉99a, the first rule to obtain 〈letter〉99a, and finally the second rule to obtain x99a.

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